Biorealistic Control of Hand Prosthesis Augments Functional Performance of Individuals With Amputation

Qi Luo; Chuanxin M Niu; Chih-Hong Chou; Wenyuan Liang; Xiaoqian Deng; Manzhao Hao; Ning Lan

doi:10.3389/fnins.2021.783505

Biorealistic Control of Hand Prosthesis Augments Functional Performance of Individuals With Amputation

Front Neurosci. 2021 Dec 14:15:783505. doi: 10.3389/fnins.2021.783505. eCollection 2021.

Authors

Qi Luo¹, Chuanxin M Niu^{1

2

3}, Chih-Hong Chou^{1

2}, Wenyuan Liang⁴, Xiaoqian Deng⁵, Manzhao Hao^{1

2}, Ning Lan^{1

2}

Affiliations

¹ Laboratory of Neurorehabilitation Engineering, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
² Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China.
³ Department of Rehabilitation Medicine, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
⁴ National Research Center for Rehabilitation Technical Aids, Beijing, China.
⁵ Guangdong Work Injury Rehabilitation Hospital, Guangzhou, China.

Abstract

The human hand has compliant properties arising from muscle biomechanics and neural reflexes, which are absent in conventional prosthetic hands. We recently proved the feasibility to restore neuromuscular reflex control (NRC) to prosthetic hands using real-time computing neuromorphic chips. Here we show that restored NRC augments the ability of individuals with forearm amputation to complete grasping tasks, including standard Box and Blocks Test (BBT), Golf Balls Test (GBT), and Potato Chips Test (PCT). The latter two were more challenging, but novel to prosthesis tests. Performance of a biorealistic controller (BC) with restored NRC was compared to that of a proportional linear feedback (PLF) controller. Eleven individuals with forearm amputation were divided into two groups: one with experience of myocontrol of a prosthetic hand and another without any. Controller performances were evaluated by success rate, failure (drop/break) rate in each grasping task. In controller property tests, biorealistic control achieved a better compliant property with a 23.2% wider range of stiffness adjustment than that of PLF control. In functional grasping tests, participants could control prosthetic hands more rapidly and steadily with neuromuscular reflex. For participants with myocontrol experience, biorealistic control yielded 20.4, 39.4, and 195.2% improvements in BBT, GBT, and PCT, respectively, compared to PLF control. Interestingly, greater improvements were achieved by participants without any myocontrol experience for BBT, GBT, and PCT at 27.4, 48.9, and 344.3%, respectively. The functional gain of biorealistic control over conventional control was more dramatic in more difficult grasp tasks of GBT and PCT, demonstrating the advantage of NRC. Results support the hypothesis that restoring neuromuscular reflex in hand prosthesis can improve neural motor compatibility to human sensorimotor system, hence enabling individuals with amputation to perform delicate grasps that are not tested with conventional prosthetic hands.

Keywords: biorealistic control; hand grasp; neuromorphic computation; neuromuscular reflex; tendon-driven prosthesis.